The RPA boost for the
Insurance industry

Better customer service through RPA

This large property/casualty company has two call centers handling thousands of monthly customer inquiries that range from direct sales to claims submissions and claims status. The company’s goals were greater agent productivity, better customer service, and higher customer service levels. However, over the past year little to no improvement in those metrics had occurred. The underlying problem was not new to us. Agents were pulling/placing data from/into a complicated web of siloed databases, Citrix environments, and legacy systems. Just to make a change of address meant involving multiple systems and databases. This was difficult for the agent to explain to callers. The result was dissatisfied customers, frustrated agents, a high CSR turnover rate and a difficult training environment. The company knew their agents needed a desktop that was fully integrated with their back office systems and databases and realized there were many CSR-specific software solutions available.

The company also knew that any solution requiring system-level integration with the back-office would be too expensive, lengthy and risky. The RPA solution solved the cost and complexity back office issues with unmatched, noninvasive Citrix, mainframe, and legacy automation technology. Each CSR is empowered to trigger instantaneous data pulls or data sharing across systems with their own agent-assist workstation robot. What used to be a complex and disconnected system of applications and databases has been gathered into a holistic, desktop view for every agent. All three key company metrics have up-ticked. Agent productivity is over 30% higher, while call time resolution is down in equal measure. Customer service surveys show consistently higher rating levels.

Non-compliant Underwriting

A regional auto insurance agency operated over 30 offices with approximately 500 employees, offering both auto insurance and program administrative services. As the company grew, process, procedure and system differences arose because some offices were the result of organic growth and others from acquisitions. Policy renewal profitability had been a management concern for some time, gaining urgency when it fell across all offices during the prior year.

An operations audit revealed poor process controls for the entire renewal workflow particularly around information collection and procedures. Process reengineering was mandated, but robots were deployed to immediately mend the most serious renewal workflow weakness: underwriting. Renewal premiums were required to reflect Kelly Blue Book valuations, but the policy was frequently ignored. Some agents didn’t underwrite at all, they simply offered a discount on the current policy. Others lowered valuations to offer attractive premiums or just made arbitrary discounts. These shortcuts not only violated company policy. The low premiums slashed profitability.

Yet there was a cure. Now, renewal policies are placed in an RPA underwriting work queue; robots pull valuations from Nada, KBB, and Edmunds, reach an average valuation by applying business rules and use that valuation with the rating engine as a basis for quoted premiums. Without waiting on process reengineering, the RPA solution achieved valuation compliance; increased precision and reliability of valuation data; brought scalability to the workflow; added six figures to profitability by producing accurate, competitive premiums.